1. Field
Embodiments of the present invention generally relate to searching a network for text and non-text data, and providing for storing and forwarding search results.
2. The Relevant Technology
Recently there has been a vast proliferation of networking connection options, for businesses and general users alike, for connecting to networks such as intranets and the Internet. Many such businesses and users position themselves as an end point, or point of interest (hereafter generally “web sites”), to whom others can connect and obtain information and other material. After several years of such end points becoming accessible of the networks, an enormous amount of information and other material is now available in an online electronic format.
A typical method for locating and reviewing such information is by way of a “web browser”, such as Netscape Navigator, Internet Explorer, Opera, and other network application programs (hereafter generally “browsers”). Unfortunately, the very richness of available information has made finding anything specific an enormously complex and tedious task. The vast number of available web sites can be likened to a beach, where a particular search seeks to locate a particular few grains of sand.
Typical search methods employ either data categorization or keyword searching. In the former, a well known-example is www-Yahoo-com, which provides broad categories and successively narrower topic areas. In the latter, there are typically two types. The first are traditional search engines such as NorthernLight-com, AltaVista-com, Excite-corn, and the like, which “crawl” web sites and index the words found therein. The second are “meta” search engines, such as SurfWax-com, DogPile-com, and the like, which execute a search across multiple search engines, and provide options for collating results. It is estimated that only 10% of all web sites are indexed. (Please note that periods within uniform resource locators (URLs) have been replaced with hyphens to prevent hypertext links in an online copy of this application.)
Unfortunately, both categorization and keyword searching have significant drawbacks. Categorization requires intervention to place a site within a relevant category or categories. Such categorization is very subjective, and therefore may result in significant omissions or misleading results when a searcher drills down to detailed categories. And, categorization is resource intensive, and therefore few web sites are categorized. Thus, typically, only “main stream” sites are categorized.
Although keyword searching does not suffer the subjective effects of categorization, such searching requires a searcher to know the correct terms to use in order to perform an effective search. And, such searches typically result in a vast number of irrelevant search results (“hits”) due to multiple uses for terms in diverse disciplines. For example, a search for “international policy” will return results concerning politics, college admission standards, international newspaper policies, foreign advocacy, etc., as each would use those terms someplace on their web page.
A further limitation to both techniques is that once the task of determining search results is accomplished, and results provided to a searcher's browser, there is no way to share those results with another party without re-executing the search. This results in a huge waste of computing resources. A related limitation is that the inherent lack of structure to web page data tends to result in web pages having large volumes of data within a given search result, where little of the web page data may actually be relevant to a particular query. In addition to making it difficult to find a relevant portion of a search result, large results can overwhelm the output capabilities of some devices (e.g., mobile devices) used for searching.